Authentic IIA Certification Exam IIA-CIA-Part3 Questions Answers

The internal audit procedures manual provides detailed policies, methodologies, and processes to guide the internal audit function. This includes the quality assurance and improvement program (QAIP), which ensures engagement performance and overall conformance with the Standards.

Option A (charter) defines authority and purpose but is not part of procedures. Option B (annual plan) is a planning document, not methodology. Option C (engagement results) are outputs, not procedures.

Data analysis in internal auditing allows auditors to assess large volumes of data, identify trends, and uncover anomalies, leading to a more comprehensive understanding of the audit area.

Definition and Role of Data Analysis in Auditing:

Data analytics in internal auditing involves using software and algorithms to analyze vast datasets for fraud detection, risk assessment, and control effectiveness.

The IIA’s GTAG on Continuous Auditing emphasizes that data-driven audits enhance visibility into operations, supporting risk-based auditing.

Why a More Holistic View?

Data analytics allows internal auditors to:

Identify patterns and trends across the entire audit area.

Detect fraud and anomalies more efficiently.

Assess risks across multiple departments simultaneously.

As per IIA Standard 1220 (Due Professional Care), auditors must consider the use of technology-based audit techniques to improve their audit scope.

Why Not Other Options?

A. It easily aligns with existing internal audit competencies to reduce expenses:

While data analytics can reduce costs, its primary benefit is enhanced audit scope and effectiveness, not just cost-cutting.

C. Its outcomes can be easily interpreted into audit conclusions:

Data analytics can enhance audit conclusions, but the interpretation still requires auditor expertise.

D. Its application increases internal auditors' adherence to the Standards:

While data analytics aligns with IIA Standards, it is not the main reason for its adoption.

IIA GTAG – Continuous Auditing: Implications for Assurance & Monitoring

IIA Standard 1220 – Due Professional Care

IIA Standard 2120 – Risk Management

Step-by-Step Justification:IIA References:Thus, the correct and verified answer is B. It provides a more holistic view of the audited area.

A systems development methodology refers to a structured approach used in software development and systems engineering to guide the design, development, and implementation of software applications.

Why Option A (Waterfall) is Correct:

Waterfall methodology is a linear and sequential systems development methodology where each phase (e.g., requirements, design, implementation, testing, deployment) must be completed before moving to the next.

It is widely established and historically one of the first software development methodologies.

Used in large-scale enterprise projects where detailed planning and structured execution are required.

Why Other Options Are Incorrect:

Option B (PRINCE2 - Projects in Controlled Environments):

Incorrect because PRINCE2 is a project management framework, not a systems development methodology.

Option C (ITIL - Information Technology Infrastructure Library):

Incorrect because ITIL is a set of IT service management (ITSM) best practices, not a software development methodology.

Option D (COBIT - Control Objectives for Information and Related Technologies):

Incorrect because COBIT is a governance framework for IT management and controls, not a development methodology.

IIA GTAG – "Auditing IT Projects and Systems Development": Highlights Waterfall as a traditional systems development methodology.

IIA’s Global Technology Audit Guide on IT Risks: Discusses software development lifecycle risks, including Waterfall methodology.

COBIT Framework – BAI03 (Manage Solutions Identification and Build): References structured methodologies like Waterfall in IT governance.

IIA References: